AI Infra & MLOps Engineer — NVAI, Kubeflow, Kubernetes

Mullers Solutions 1; Dubai; On-site; AED 391,000 - 614,000; Full time

Job summary

Müller’s Solutions is seeking an AI Infrastructure & MLOps Engineer for a 6-month contract in Dubai. The role is primarily operations-focused (90%), with hands-on involvement in implementation, configuration, and setup of AI infrastructure and MLOps workflows.

You will manage, operate, and guide deployment of a strategic AI environment, working closely with the customer as a technical advisor and hands-on engineer, with duties including monitoring and maintaining AI workloads and setting up

Qualifications

• 4–6 years of practical experience in Python and Jupyter Notebook/JupyterLab.
• Strong Kubernetes experience and familiarity with Kubeflow/MLflow.
• Proven ability to install, configure, and operate AI infrastructure and workflows.

Responsibilities

• Operate and maintain AI infrastructure and MLOps platforms in a production environment.
• Monitor, manage, and troubleshoot Kubernetes-based AI workloads.
• Perform Acceptance Testing Planning and Execution for AI infrastructure and platforms.
• Ensure stability, performance, and availability of AI systems.
• Support day-to-day operational tasks across compute, storage, and networking layers.
• Install and configure NVIDIA Enterprise AI Stack (NVAI).
• Configure and manage MLOps platforms such as Kubeflow and MLflow.
• Assist in setting up end-to-end AI workflows, including data pipelines.
• Support the initial implementation phase of the AI environment.
• Act as a technical guide and advisor to the customer during the early stages of their AI adoption.

Skills

Python

Jupyter Notebook / JupyterLab

Kubernetes

Kubeflow

MLflow

NVIDIA Enterprise AI Stack

Ubuntu Linux

Tools

QFLOW

Kubeflow

MLflow

Job description

Müller’s Solutions is seeking an AI Infrastructure & MLOps Engineer for a 6-month contract in Dubai. The role is primarily operations-focused (90%), with hands-on involvement in implementation, configuration, and setup of AI infrastructure and MLOps workflows.

You will manage, operate, and guide deployment of a strategic AI environment, working closely with the customer as a technical advisor and hands-on engineer, with duties including monitoring and maintaining AI workloads and setting up